Exploiting Hardware Heterogeneity within the Same Instance Type of Amazon EC2
|
|
- Sherman Matthews
- 8 years ago
- Views:
Transcription
1 Exploiting Hardware Heterogeneity within the Sae Instance Type of Aazon EC2 Zhonghong Ou, Hao Zhuang, Jukka K. Nurinen, Antti Ylä-Jääski, Pan Hui Aalto University, Finland; Deutsch Teleko Laboratories, Gerany Abstract Cloud coputing providers ight start with nearhoogeneous hardware environent. Over tie, the hoogeneous environent will ost likely evolve into heterogeneous one because of possible upgrades and replaceent of outdated hardware. In turn, the hardware heterogeneity will result into perforance variation. In this paper, we look into the hardware heterogeneity and the corresponding perforance variation within the sae instance type of Aazon Elastic Copute Cloud (Aazon EC2). Standard large instance is selected as the exaple. We find out that there exist three different subtypes of hardware configuration in the standard large instance. Through a set of detailed icro-benchark and application-level benchark easureents, we observe that the perforance variation within the sae sub-type of instance is relatively sall, whilst the variation between different sub-types can be up to 60%. By selecting better-perforing instances to coplete the sae task, end-users of Aazon EC2 platfor can achieve up to 30% cost saving. 1 Introduction Cloud coputing attracts a significant aount of attention fro industry, acadeia, and edia because of its on-deand, pay-as-you-go, etc, characteristics. As a representative and one of the ost widely adopted public cloud platfors, Aazon Elastic Copute Cloud (Aazon EC2) has been used for a host of sall and ediusized enterprises (SMEs) for various usages. Aazon EC2 was introduced in 2006, and supports a wide arrange of instance types. Naturally, these different types of instances are likely hosted by heterogeneous hardware. Over tie, because of hardware upgrade and replaceent, it would be interesting to investigate the following issues: (1) Does the sae type of instance utilize hoogeneous or heterogeneous hardware configuration? (2) If heterogeneous hardware is used, what is the resulting perforance variation? In this paper, we try to answer the aforeentioned two questions by utilizing the standard large instance type, i.e. 1.large. Siilar results are observed for the other types of instances within the sae standard faily, including sall (1.sall), and extra large (1.xlarge) instances. Our contributions are as follows: (1) We observe that within the sae instance type, Aazon EC2 uses heterogeneous hardware to host the instances. (2) The variation of the sae sub-type of instances, i.e. hosted by identical hardware, is relatively sall, whilst the variation aong different sub-types of instances, i.e. hosted by heterogeneous hardware, can reach up to 60%. (3) Copared with taking the rando instances assigned by Aazon EC2 platfor, by selecting betterperforing instances to coplete the sae task, EC2 users can acquire up to 30% of cost saving. The rest of the paper is structured as follows. In Section 2, we present background and related literature of Aazon EC2 study. Section 3 details the icrobenchark easureents and application-level bencharks. Section 4 analyzes the potential cost saving for EC2 end-users. In Section 5 we conclude the paper and present ideas for future work. 2 Related Work Several studies have been conducted to analyze various aspects of Aazon EC2. Garfinkel [4] conducted a easureent study of various Aazon Web Services (AWS) to evaluate the feasibility and cost of oving a largescale research application fro localized server to Aazon offering. Palankar et al. [8] perfored easureents focusing on Aazon S3 to testify its ability to provide stable storage support for large-scale scientific
2 coputation application. Walker [12] studied the perforance of Aazon EC2 high-perforance cluster copute instances against a locally configured equivalent processors cluster, and showed that there exists a perforance gap between the EC2 provisioned cluster and local traditional scientific cluster. Wang et al. [13] presented a easureent study on the ipact of virtualization on Aazon EC2 platfor. Their findings indicated that virtualization causes instability and variation to network throughput and packet delay. Li et al. [7] developed a perforance and cost coparator, i.e. CloudCp, to easure cloud services fro different cloud providers. Their study deonstrated that there was no single winner who outperfored the other counterparts in all aspects of its cloud service offerings. Cooper et al. [2] developed Yahoo! Cloud Serving Benchark (YCSB) fraework to facilitate perforance coparison. Barker et al. [1] analyzed the ipact of virtualization on the perforance of latency sensitive applications in the cloud. Furtherore, in exploiting heterogeneity in the cloud, there exist several studies. Suneja et al. [10] proposed to use Graphics Processing Uint (GPU) acceleration to speed up cloud anageent tasks in Virtual Machine Monitor (VMM). Lee et al. [6] introduced a scheduling echanis in the cloud that takes into consideration heterogeneity of the underlying platfor and workloads. Through atheatical odeling, Yeo et al. [14] found out that in order to achieve optial perforance, the perforance variation aong a heterogeneous cloud infrastructure should be no larger than three ties. To the best of our knowledge, there is no work focusing on exploiting the heterogeneity within the sae instance type of Aazon EC2, which otivates our work in this paper. 3 Micro-benchark In this section, we first analyze the hardware configuration of Aazon EC2. Then we utilize several icrobenchark tools to evaluate the perforance of various sub-types of instances. Specifically, standard large instance (1.large) is selected as the representative for perforance evaluation. 3.1 Hardware Configurations of EC2 We acquire the hardware inforation of Aazon EC2 instances by using cpuid coand, a non-trapping instruction that can be used in user ode without triggering trap to the underlying processor. Thus, the hypervisor does not capture the instruction and return odified results. Furtherore, we run cat /proc/cpuinfo coand to verify the results fro cpuid. The CPU odels fro both sources are identical, and the results are listed Table 1: Hardware configuration Instance type CPU odel %(2011) %(2012) E % 12% 1.sall E % 38% E5645 3% 30% 2218HE 18% 20% E % 40% E % 17% 1.large E5645 5% 42% 2218HE 4% 1% 270 4% - E % 6% 1.xlarge E % 46% E % 48% 270 2% - in Table 1. It is noteworthy that we only list the standard instance faily in Table 1. Diversified hardware is also used in high-cpu instance faily (c1.ediu and c1.xlarge). We exclude the due to space liit. Furtherore, the high-eory instances use identical Intel X5550 processors, and the cluster copute and cluster GPU instances both use Intel Xeon X5570 processors. We collected hardware inforation within two periods of tie to investigate the hardware changes fro hardware upgrade or replaceent. One period is fro April through July in 2011; the other one is fro January through March in For each period, we collect hardware inforation of 200 instances for each instance type, covering all availability zones in the US (Virginia) east region. The percentage of each CPU odel is shown in %(2011) and %(2012) coluns, respectively. The 2218HE and 270 odels are fro AMD Opteron series, whilst the rest are fro Intel Xeon series. Fro Table 1, it is clearly shown that newer processor odels are replacing older ones gradually, whilst the older ones are likely used for saller instances in the sae instance faily. For exaple, in 1.large instance, the AMD Opteron 270 (released in 2005) processor that was found in 2011 is no longer accessible in 2012, whilst the Intel Xeon E5645 (released Q1 10) CPU odel is ore frequently accessible in 2012 than in This trend is siilar in all standard (including 1.sall, 1.large, and 1.xlarge) and high-cpu (including c1.ediu and c1.xlarge) instances. Furtherore, we notice that the probability of a specific type of processor, e.g. E5645, significantly varies in different availability zones. In one availability zone, we can acquire 95% of instances hosted by E5645 achines, whilst in another zone, the probability of E5645 instances is as low as 10%. We conjecture that the availability zone with 95% of E5645 achines is a newly built 2
3 Score Instance E E E E E E Figure 1: UnixBench score, one and two processes Requests per second 6 x E5645 E5430 E Nuber of clients Figure 2: Redis SET operation data center within the US east region. The interesting question to ask is whether the heterogeneous hardware configuration within the sae instance type leads to diversified perforance. We select the 1.large instance as the exaple to evaluate perforance because this instance has a relatively large aount of eory and can be used in various general applications. 3.2 Micro-bencharks We use several icro-benchark tools to easure the perforance of 1.large instance, including UnixBench [11] to easure the CPU, Redis [9] to easure the eory, and Dbench [3] to easure the disk subsystes. To provide apples-to-apples coparison, we use the sae Aazon Machine Iage with CentOS5.6 in all the instances tested. The benchark is the only process running when we conduct the easureents. CPU perforance: UnixBench [11] utilizes ultiple tests to easure various aspects of the syste s perforance, priarily CPU s perforance. The test results are copared to the baseline syste to produce an index value. The entire set of index values are then cobined to ake a coposite index for the syste. To easure the likely diversity of instances fro the sae hardware configuration, we choose 20 instances fro each subtype of instance, i.e. E5507, E5430, and E5645. The results of the UnixBench benchark are shown in Fig. 1. The figure clearly deonstrates that the differences aongst the sae sub-type of instances, e.g. E5507, is sall, whilst the differences between different sub-types are significant. If one process is running, E5430 and E5645 are coparable in ters of perforance, whilst they are approxiately 1.15 ties of the perforance of E5507. When two processes are running, E5645 outperfors E5430, whilst E5430 further outperfors E5507. The perforance variation in ties is 1.21, and 1.1 ties for E5645, and E5430, respectively, wherein E5507 is taken as the baseline. Meory perforance: Redis [9] is an in-eory key-value store that has the benchark utility to siulate ultiple concurrent clients to send requests (e.g. SET, and GET) at the sae tie. In our easureents, we perfor 100,000 requests and vary the nuber of concurrent clients. Rando key is used to perfor the operations. The detailed results fro GET operations are depicted in Fig. 2. The results fro other operation are siilar to GET operation. Siilar to Fig. 1, in eory operations, E5645 instances outperfor E5430 and E5507 instances. The eory perforance of E5645 is 1.5 ties of that of E5507, whilst E5430 is 1.14 ties of E5507. Disk perforance: The results fro Dbench [3] show siilar trends as the Unixbench, and Redis. E5645 instances can provide disk throughput 1.25 ties as high as E5507 instances, whilst E5430 provides coparable disk throughput as E Application-level Benchark We use Httperf [5] to easure the Web server throughput. Dynaic HTTP request is used to ake the processor busy. Dynaic request eans after receiving a request fro a client, the Web server perfors a atheatical suation fro 1 through 100, and then returns the result to the client. Thus, the dynaic Web test is CPU-bound rather than network-bound. To try to avoid potential bottleneck fro client achine, we use a high- CPU ediu instance fro the sae zone acting as the client. The Httperf throughput results are depicted in Fig. 3. The figure deonstrates that the advantages fro separate subsystes, e.g. CPU, eory and disk, are accuulated at application-level, where E5645 is 1.6 ties as efficient as E5507 and E5430 is 1.2 ties as E
4 Response/sec Notation f h n p i x i C E5645 E5430 E Request/sec 4 Cost Analysis Figure 3: Httperf perforance Table 2: Notations Definition Hourly cost of an instance Nuber of hours to run Nuber of different instances Nuber of instances needed with worst perforance Probability of instances hosted with a specific hardware Perforance variation copared to the baseline instance The total cost Now we are aware that there exists various hardware configuration in the sae instance type. We analyze the potential cost saving by seeking for the best-perforing instances in the sae instance type. The worst-perforing instance is used as the baseline, the other instances are x (no less than 1) ties as fast as the baseline instance. We use the notations defined in Table 2. Given the sae aount of task (coputation, counication etc), with better-perforing instances, the task can be copleted with two alternatives: (1) saller nuber of instances running for the sae aount of tie; (2) sae nuber of instances running for shorter period of tie. Fro the cost perspective, these two alternatives are the sae. We take the first alternative as the exaple. The expected value of the perforance of a rando instance is defined as follows: E(X) = i=1 x i p i (1) The total cost of copleting the task, equivalent to n h hours work, using rando instances can be deduced as follows: C rando = n h f /E(X) (2) If we ai to select the best-perforing instances to coplete the task, the cost of this optiized scenario is: C opt = n h f /x opt (3) Furtherore, the trial and error testing process results in extra cost for the optiized scenario. As in Aazon EC2, the less than one hour usage is rounded up to and charged as one hour. Thus, the extra cost of finding n best-perforing instances is: C extra = n f /p opt (4) Here we assue that the test of finding one fast instance takes no ore than one hour and the jobs are relatively sall to the population of available servers. As a atter of fact, we can siply request for one instance fro Aazon, then inspect its cpuid. If the instance is not the best-perforing one, we siply discard it and request for another one. The potential cost saving is: C saving = C rando C opt C extra (5) Put Eq. 1, Eq. 2, Eq. 3, and Eq. 4 in Eq. 5, we can deduce the following equation: C saving = (h/( i=1 x i p i ) h/x opt 1/p opt ) n f (6) Understandably, if one fast instance is able to acquire cost gain, the total cost gain achievable fro ultiple instances grows linearly with the nuber of instances. This is also applicable to the price of the instance. Again, take the 1.large instance as the exaple. There are three different sub-types of instances, E5430, E5507, and E5645. The probability of each subtype of instance is 17%, 40%, and 42%, respectively. The unit cost of a regular 1.large instance (excluding reserved instances and spot instances) is $0.34/hour. The worstperforing instance is E5507, thus it is taken as the baseline. On average, E5430 and E5645 is 1.1 and 1.4 ties, respectively, as fast as E5507. Put all these values in Eq. 6, we can acquire the following equation: C saving = 0.34 n ( h 2.38) (7) In order to achieve cost saving, the requireent is C saving > 0, then we can get the necessity: h > That is to say, given the aforeentioned probability of each subtype of instance and its respective perforance, it starts to ake sense fro cost perspective to select E5645 instances to coplete the task if the required tie is larger than 18 hours. 4
5 Cost saving(%) p=0.1 p=0.5 p= Perforance variation (ties) Figure 4: Cost saving analysis Through two periods of several-onth easureents in 2011 and 2012, we found out that Aazon EC2 uses diversified hardware to host the sae type of instance. The hardware diversity results in perforance variation. In general, the variation between the fast instances and slow instances can reach 40%. In soe applications, the variation can even approach up to 60%. By selecting fast instances within the sae instance type, Aazon EC2 users can acquire up to 30% of cost saving, if the fast instances have a relatively low probability. In the future, we plan to investigate the scheduling echanis and analyze its ipact on the perforance of Aazon EC2 instances. If we have a task requires 100 E5507 coparable 1.large instances to coplete in a year (24hours/day*365days/year=8760 hours), the potential cost saving for the whole year is $40664, a 16% cost saving in percentage. Recall fro section 3.1 that different hardware is not distributed uniforly aong all the availability zones, but rather in soe zone one type of hardware doinates the whole zone, whist in another zone, another type of hardware doinates. Thus, it would also be interesting to analyze two types of hardware (e.g. E5507 and E5645) and investigate the axiu cost saving achievable. The result is depicted in Fig. 4, wherein p stands for the probability of the fast instances (e.g. E5645), and x-axis stands for the perforance variation in ties. Understandably, if the fast instances account for the ajority of the overall instances, e.g. p = 0.9, without a selection process, the probability of acquiring a fast instance is very high. Thus, the perforance is close to the optial situation with the selection process, and the cost saving achievable is trivial. However, as the fast instances account for less proportion of the overall instances, the cost saving achievable is becoing significant. In the case of p = 0.1, if the fast instance is 10 ties as fast as the slow instance, the cost saving is as high as 80%. Obviously, this is an unrealistic situation with all the efforts Aazon contributes to ake the sae type of instances function closely. Fro section 3.2 and 3.3, we know that ties variation is highly possible. With 1.5 ties variation, the achievable cost saving can reach 30%. For SMEs, which are the ajor custoers of Aazon EC2 platfor, this saving has a big ipact. 5 Conclusions In this paper, we investigated the hardware heterogeneity within the sae instance type of Aazon EC2. Standard large instance (1.large) was taken as the exaple. 6 Acknowledgents The research conducted in this paper has been funded by the Finnish funding agency for technology and innovation (Tekes) in Massive Scale Machine-to-Machine Service (MAMMotH) project (Dnro 820/31/2011). References [1] BARKER, S., AND SHENOY, P. Epirical evaluation of latencysensitive application perforance in the cloud. Proceedings of MMSys (2010), [2] COOPER, B., SILBERSTEIN, A., TAM, E., RAMAKRISHNAN, R., AND SEARS, R. Bencharking cloud serving systes with YCSB. Proceedings of SoCC (2010), [3] Dbench. [4] GARFINKEL, S. L. An evaluation of Aazon s grid coputing services: EC2, S3 and SQS. Tech. Rep. tr-08-07, Harvard University, [5] Httperf. httperf/. [6] LEE, G., CHUN, B., AND KATZ, R. H. Heterogeneity-aware resource allocation and scheduling in the cloud. Proceedings of HotCloud (2011), 1 5. [7] LI, A., YANG, X., KANDULA, S., AND ZHANG, M. CloudCp: coparing public cloud providers. Proceedings of IMC (2010), [8] PALANKAR, M., IAMNITCHI, A., RIPEANU, M., AND GARFINKEL, S. Aazon S3 for science grids: a viable solution? Proceedings of the 2008 international workshop on Data-aware distributed coputing (2008), [9] Redis. [10] SUNEJA, S., BARON, E., AND E. DE LARA, R. J. Accelerating the cloud with heterogeneous coputing. Proceedings of Hot- Cloud (2011), 1 5. [11] Unixbench. [12] WALKER, E. Bencharking aazon EC2 for high-perforance scientific coputing. USENIX ;login: 33, 5 (2008), [13] WANG, G., AND NG, T. The ipact of virtualization on network perforance of aazon ec2 data center. Proceedings of INFO- COM (2010), 1 9. [14] YEO, S., AND LEE, H. Using atheatical odeling in provisioning a heterogeneous cloud coputing environent. Coputer 44, 8 (2011),
An Innovate Dynamic Load Balancing Algorithm Based on Task
An Innovate Dynaic Load Balancing Algorith Based on Task Classification Hong-bin Wang,,a, Zhi-yi Fang, b, Guan-nan Qu,*,c, Xiao-dan Ren,d College of Coputer Science and Technology, Jilin University, Changchun
More informationEnergy Efficient VM Scheduling for Cloud Data Centers: Exact allocation and migration algorithms
Energy Efficient VM Scheduling for Cloud Data Centers: Exact allocation and igration algoriths Chaia Ghribi, Makhlouf Hadji and Djaal Zeghlache Institut Mines-Téléco, Téléco SudParis UMR CNRS 5157 9, Rue
More informationThe Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs
Send Orders for Reprints to reprints@benthascience.ae 206 The Open Fuels & Energy Science Journal, 2015, 8, 206-210 Open Access The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic
More informationThe Benefit of SMT in the Multi-Core Era: Flexibility towards Degrees of Thread-Level Parallelism
The enefit of SMT in the Multi-Core Era: Flexibility towards Degrees of Thread-Level Parallelis Stijn Eyeran Lieven Eeckhout Ghent University, elgiu Stijn.Eyeran@elis.UGent.be, Lieven.Eeckhout@elis.UGent.be
More informationThis paper studies a rental firm that offers reusable products to price- and quality-of-service sensitive
MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol., No. 3, Suer 28, pp. 429 447 issn 523-464 eissn 526-5498 8 3 429 infors doi.287/so.7.8 28 INFORMS INFORMS holds copyright to this article and distributed
More informationSearching strategy for multi-target discovery in wireless networks
Searching strategy for ulti-target discovery in wireless networks Zhao Cheng, Wendi B. Heinzelan Departent of Electrical and Coputer Engineering University of Rochester Rochester, NY 467 (585) 75-{878,
More informationSoftware Quality Characteristics Tested For Mobile Application Development
Thesis no: MGSE-2015-02 Software Quality Characteristics Tested For Mobile Application Developent Literature Review and Epirical Survey WALEED ANWAR Faculty of Coputing Blekinge Institute of Technology
More informationAnalyzing Spatiotemporal Characteristics of Education Network Traffic with Flexible Multiscale Entropy
Vol. 9, No. 5 (2016), pp.303-312 http://dx.doi.org/10.14257/ijgdc.2016.9.5.26 Analyzing Spatioteporal Characteristics of Education Network Traffic with Flexible Multiscale Entropy Chen Yang, Renjie Zhou
More informationDynamic Placement for Clustered Web Applications
Dynaic laceent for Clustered Web Applications A. Karve, T. Kibrel, G. acifici, M. Spreitzer, M. Steinder, M. Sviridenko, and A. Tantawi IBM T.J. Watson Research Center {karve,kibrel,giovanni,spreitz,steinder,sviri,tantawi}@us.ib.co
More informationEvaluating Inventory Management Performance: a Preliminary Desk-Simulation Study Based on IOC Model
Evaluating Inventory Manageent Perforance: a Preliinary Desk-Siulation Study Based on IOC Model Flora Bernardel, Roberto Panizzolo, and Davide Martinazzo Abstract The focus of this study is on preliinary
More informationAn Improved Decision-making Model of Human Resource Outsourcing Based on Internet Collaboration
International Journal of Hybrid Inforation Technology, pp. 339-350 http://dx.doi.org/10.14257/hit.2016.9.4.28 An Iproved Decision-aking Model of Huan Resource Outsourcing Based on Internet Collaboration
More informationA Scalable Application Placement Controller for Enterprise Data Centers
W WWW 7 / Track: Perforance and Scalability A Scalable Application Placeent Controller for Enterprise Data Centers Chunqiang Tang, Malgorzata Steinder, Michael Spreitzer, and Giovanni Pacifici IBM T.J.
More informationApplying Multiple Neural Networks on Large Scale Data
0 International Conference on Inforation and Electronics Engineering IPCSIT vol6 (0) (0) IACSIT Press, Singapore Applying Multiple Neural Networks on Large Scale Data Kritsanatt Boonkiatpong and Sukree
More informationPERFORMANCE METRICS FOR THE IT SERVICES PORTFOLIO
Bulletin of the Transilvania University of Braşov Series I: Engineering Sciences Vol. 4 (53) No. - 0 PERFORMANCE METRICS FOR THE IT SERVICES PORTFOLIO V. CAZACU I. SZÉKELY F. SANDU 3 T. BĂLAN Abstract:
More informationModeling Parallel Applications Performance on Heterogeneous Systems
Modeling Parallel Applications Perforance on Heterogeneous Systes Jaeela Al-Jaroodi, Nader Mohaed, Hong Jiang and David Swanson Departent of Coputer Science and Engineering University of Nebraska Lincoln
More informationResearch Article Performance Evaluation of Human Resource Outsourcing in Food Processing Enterprises
Advance Journal of Food Science and Technology 9(2): 964-969, 205 ISSN: 2042-4868; e-issn: 2042-4876 205 Maxwell Scientific Publication Corp. Subitted: August 0, 205 Accepted: Septeber 3, 205 Published:
More informationCooperative Caching for Adaptive Bit Rate Streaming in Content Delivery Networks
Cooperative Caching for Adaptive Bit Rate Streaing in Content Delivery Networs Phuong Luu Vo Departent of Coputer Science and Engineering, International University - VNUHCM, Vietna vtlphuong@hciu.edu.vn
More informationASIC Design Project Management Supported by Multi Agent Simulation
ASIC Design Project Manageent Supported by Multi Agent Siulation Jana Blaschke, Christian Sebeke, Wolfgang Rosenstiel Abstract The coplexity of Application Specific Integrated Circuits (ASICs) is continuously
More informationOnline Bagging and Boosting
Abstract Bagging and boosting are two of the ost well-known enseble learning ethods due to their theoretical perforance guarantees and strong experiental results. However, these algoriths have been used
More informationCLOSED-LOOP SUPPLY CHAIN NETWORK OPTIMIZATION FOR HONG KONG CARTRIDGE RECYCLING INDUSTRY
CLOSED-LOOP SUPPLY CHAIN NETWORK OPTIMIZATION FOR HONG KONG CARTRIDGE RECYCLING INDUSTRY Y. T. Chen Departent of Industrial and Systes Engineering Hong Kong Polytechnic University, Hong Kong yongtong.chen@connect.polyu.hk
More informationUse of extrapolation to forecast the working capital in the mechanical engineering companies
ECONTECHMOD. AN INTERNATIONAL QUARTERLY JOURNAL 2014. Vol. 1. No. 1. 23 28 Use of extrapolation to forecast the working capital in the echanical engineering copanies A. Cherep, Y. Shvets Departent of finance
More informationMedia Adaptation Framework in Biofeedback System for Stroke Patient Rehabilitation
Media Adaptation Fraework in Biofeedback Syste for Stroke Patient Rehabilitation Yinpeng Chen, Weiwei Xu, Hari Sundara, Thanassis Rikakis, Sheng-Min Liu Arts, Media and Engineering Progra Arizona State
More informationA framework for performance monitoring, load balancing, adaptive timeouts and quality of service in digital libraries
Int J Digit Libr (2000) 3: 9 35 INTERNATIONAL JOURNAL ON Digital Libraries Springer-Verlag 2000 A fraework for perforance onitoring, load balancing, adaptive tieouts and quality of service in digital libraries
More informationarxiv:0805.1434v1 [math.pr] 9 May 2008
Degree-distribution stability of scale-free networs Zhenting Hou, Xiangxing Kong, Dinghua Shi,2, and Guanrong Chen 3 School of Matheatics, Central South University, Changsha 40083, China 2 Departent of
More informationStudy on the development of statistical data on the European security technological and industrial base
Study on the developent of statistical data on the European security technological and industrial base Security Sector Survey Analysis: France Client: European Coission DG Migration and Hoe Affairs Brussels,
More informationMachine Learning Applications in Grid Computing
Machine Learning Applications in Grid Coputing George Cybenko, Guofei Jiang and Daniel Bilar Thayer School of Engineering Dartouth College Hanover, NH 03755, USA gvc@dartouth.edu, guofei.jiang@dartouth.edu
More informationImplementation of Active Queue Management in a Combined Input and Output Queued Switch
pleentation of Active Queue Manageent in a obined nput and Output Queued Switch Bartek Wydrowski and Moshe Zukeran AR Special Research entre for Ultra-Broadband nforation Networks, EEE Departent, The University
More informationReal Time Target Tracking with Binary Sensor Networks and Parallel Computing
Real Tie Target Tracking with Binary Sensor Networks and Parallel Coputing Hong Lin, John Rushing, Sara J. Graves, Steve Tanner, and Evans Criswell Abstract A parallel real tie data fusion and target tracking
More informationA Multi-Core Pipelined Architecture for Parallel Computing
Parallel & Cloud Coputing PCC Vol, Iss A Multi-Core Pipelined Architecture for Parallel Coputing Duoduo Liao *1, Sion Y Berkovich Coputing for Geospatial Research Institute Departent of Coputer Science,
More informationAn Approach to Combating Free-riding in Peer-to-Peer Networks
An Approach to Cobating Free-riding in Peer-to-Peer Networks Victor Ponce, Jie Wu, and Xiuqi Li Departent of Coputer Science and Engineering Florida Atlantic University Boca Raton, FL 33431 April 7, 2008
More informationInternational Journal of Management & Information Systems First Quarter 2012 Volume 16, Number 1
International Journal of Manageent & Inforation Systes First Quarter 2012 Volue 16, Nuber 1 Proposal And Effectiveness Of A Highly Copelling Direct Mail Method - Establishent And Deployent Of PMOS-DM Hisatoshi
More informationExtended-Horizon Analysis of Pressure Sensitivities for Leak Detection in Water Distribution Networks: Application to the Barcelona Network
2013 European Control Conference (ECC) July 17-19, 2013, Zürich, Switzerland. Extended-Horizon Analysis of Pressure Sensitivities for Leak Detection in Water Distribution Networks: Application to the Barcelona
More informationFuzzy Sets in HR Management
Acta Polytechnica Hungarica Vol. 8, No. 3, 2011 Fuzzy Sets in HR Manageent Blanka Zeková AXIOM SW, s.r.o., 760 01 Zlín, Czech Republic blanka.zekova@sezna.cz Jana Talašová Faculty of Science, Palacký Univerzity,
More informationThe AGA Evaluating Model of Customer Loyalty Based on E-commerce Environment
6 JOURNAL OF SOFTWARE, VOL. 4, NO. 3, MAY 009 The AGA Evaluating Model of Custoer Loyalty Based on E-coerce Environent Shaoei Yang Econoics and Manageent Departent, North China Electric Power University,
More informationMarkov Models and Their Use for Calculations of Important Traffic Parameters of Contact Center
Markov Models and Their Use for Calculations of Iportant Traffic Paraeters of Contact Center ERIK CHROMY, JAN DIEZKA, MATEJ KAVACKY Institute of Telecounications Slovak University of Technology Bratislava
More informationImpact of Processing Costs on Service Chain Placement in Network Functions Virtualization
Ipact of Processing Costs on Service Chain Placeent in Network Functions Virtualization Marco Savi, Massio Tornatore, Giacoo Verticale Dipartiento di Elettronica, Inforazione e Bioingegneria, Politecnico
More informationGenerating Certification Authority Authenticated Public Keys in Ad Hoc Networks
SECURITY AND COMMUNICATION NETWORKS Published online in Wiley InterScience (www.interscience.wiley.co). Generating Certification Authority Authenticated Public Keys in Ad Hoc Networks G. Kounga 1, C. J.
More informationCRM FACTORS ASSESSMENT USING ANALYTIC HIERARCHY PROCESS
641 CRM FACTORS ASSESSMENT USING ANALYTIC HIERARCHY PROCESS Marketa Zajarosova 1* *Ph.D. VSB - Technical University of Ostrava, THE CZECH REPUBLIC arketa.zajarosova@vsb.cz Abstract Custoer relationship
More informationProtecting Small Keys in Authentication Protocols for Wireless Sensor Networks
Protecting Sall Keys in Authentication Protocols for Wireless Sensor Networks Kalvinder Singh Australia Developent Laboratory, IBM and School of Inforation and Counication Technology, Griffith University
More informationResource Allocation in Wireless Networks with Multiple Relays
Resource Allocation in Wireless Networks with Multiple Relays Kağan Bakanoğlu, Stefano Toasin, Elza Erkip Departent of Electrical and Coputer Engineering, Polytechnic Institute of NYU, Brooklyn, NY, 0
More informationHow To Balance Over Redundant Wireless Sensor Networks Based On Diffluent
Load balancing over redundant wireless sensor networks based on diffluent Abstract Xikui Gao Yan ai Yun Ju School of Control and Coputer Engineering North China Electric ower University 02206 China Received
More informationReliability Constrained Packet-sizing for Linear Multi-hop Wireless Networks
Reliability Constrained acket-sizing for inear Multi-hop Wireless Networks Ning Wen, and Randall A. Berry Departent of Electrical Engineering and Coputer Science Northwestern University, Evanston, Illinois
More informationConstructing Services with Interposable Virtual Hardware
Constructing Services with Interposable Virtual Hardware Andrew Whitaker, Richard S. Cox, Marianne Shaw, and Steven D. Gribble University of Washington {andrew,rick,ar,gribble}@cs.washington.edu Abstract
More informationConsiderations on Distributed Load Balancing for Fully Heterogeneous Machines: Two Particular Cases
Considerations on Distributed Load Balancing for Fully Heterogeneous Machines: Two Particular Cases Nathanaël Cheriere Departent of Coputer Science ENS Rennes Rennes, France nathanael.cheriere@ens-rennes.fr
More informationBotnets Detection Based on IRC-Community
Botnets Detection Based on IRC-Counity Wei Lu and Ali A. Ghorbani Network Security Laboratory, Faculty of Coputer Science University of New Brunswick, Fredericton, NB E3B 5A3, Canada {wlu, ghorbani}@unb.ca
More informationImage restoration for a rectangular poor-pixels detector
Iage restoration for a rectangular poor-pixels detector Pengcheng Wen 1, Xiangjun Wang 1, Hong Wei 2 1 State Key Laboratory of Precision Measuring Technology and Instruents, Tianjin University, China 2
More informationCPU Animation. Introduction. CPU skinning. CPUSkin Scalar:
CPU Aniation Introduction The iportance of real-tie character aniation has greatly increased in odern gaes. Aniating eshes ia 'skinning' can be perfored on both a general purpose CPU and a ore specialized
More informationThe Application of Bandwidth Optimization Technique in SLA Negotiation Process
The Application of Bandwidth Optiization Technique in SLA egotiation Process Srecko Krile University of Dubrovnik Departent of Electrical Engineering and Coputing Cira Carica 4, 20000 Dubrovnik, Croatia
More informationStudy on the development of statistical data on the European security technological and industrial base
Study on the developent of statistical data on the European security technological and industrial base Security Sector Survey Analysis: Poland Client: European Coission DG Migration and Hoe Affairs Brussels,
More informationEntity Search Engine: Towards Agile Best-Effort Information Integration over the Web
Entity Search Engine: Towards Agile Best-Effort Inforation Integration over the Web Tao Cheng, Kevin Chen-Chuan Chang University of Illinois at Urbana-Chapaign {tcheng3, kcchang}@cs.uiuc.edu. INTRODUCTION
More informationRECURSIVE DYNAMIC PROGRAMMING: HEURISTIC RULES, BOUNDING AND STATE SPACE REDUCTION. Henrik Kure
RECURSIVE DYNAMIC PROGRAMMING: HEURISTIC RULES, BOUNDING AND STATE SPACE REDUCTION Henrik Kure Dina, Danish Inforatics Network In the Agricultural Sciences Royal Veterinary and Agricultural University
More informationMethod of supply chain optimization in E-commerce
MPRA Munich Personal RePEc Archive Method of supply chain optiization in E-coerce Petr Suchánek and Robert Bucki Silesian University - School of Business Adinistration, The College of Inforatics and Manageent
More informationManaging Complex Network Operation with Predictive Analytics
Managing Coplex Network Operation with Predictive Analytics Zhenyu Huang, Pak Chung Wong, Patrick Mackey, Yousu Chen, Jian Ma, Kevin Schneider, and Frank L. Greitzer Pacific Northwest National Laboratory
More informationIT SOURCING PORTFOLIO MANAGEMENT FOR IT SERVICES PROVIDERS - A RISK/COST PERSPECTIVE
IT SOURCING PORTFOLIO MANAGEMENT FOR IT SERVICES PROVIDERS - A RISK/COST PERSPECTIVE Copleted Research Paper Steffen Zierann Arne Katzarzik Dennis Kundisch Abstract Utilizing a global IT sourcing strategy
More informationIEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, ACCEPTED FOR PUBLICATION 1. Secure Wireless Multicast for Delay-Sensitive Data via Network Coding
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, ACCEPTED FOR PUBLICATION 1 Secure Wireless Multicast for Delay-Sensitive Data via Network Coding Tuan T. Tran, Meber, IEEE, Hongxiang Li, Senior Meber, IEEE,
More informationAirline Yield Management with Overbooking, Cancellations, and No-Shows JANAKIRAM SUBRAMANIAN
Airline Yield Manageent with Overbooking, Cancellations, and No-Shows JANAKIRAM SUBRAMANIAN Integral Developent Corporation, 301 University Avenue, Suite 200, Palo Alto, California 94301 SHALER STIDHAM
More informationDesign of Model Reference Self Tuning Mechanism for PID like Fuzzy Controller
Research Article International Journal of Current Engineering and Technology EISSN 77 46, PISSN 347 56 4 INPRESSCO, All Rights Reserved Available at http://inpressco.co/category/ijcet Design of Model Reference
More informationRed Hat Enterprise Linux: Creating a Scalable Open Source Storage Infrastructure
Red Hat Enterprise Linux: Creating a Scalable Open Source Storage Infrastructure By Alan Radding and Nick Carr Abstract This paper discusses the issues related to storage design and anageent when an IT
More informationUS 20100077068A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2010/0077068 A1 Saha et al. (43) Pub. Date: Mar.
US 20100077068A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2010/0077068 A1 Saha et al. (43) Pub. Date: Mar. 25, 2010 (54) PROCESSING OF SERVICE-ORIENTED Publication Classi?cation
More informationMarkovian inventory policy with application to the paper industry
Coputers and Cheical Engineering 26 (2002) 1399 1413 www.elsevier.co/locate/copcheeng Markovian inventory policy with application to the paper industry K. Karen Yin a, *, Hu Liu a,1, Neil E. Johnson b,2
More informationAn Optimal Task Allocation Model for System Cost Analysis in Heterogeneous Distributed Computing Systems: A Heuristic Approach
An Optial Tas Allocation Model for Syste Cost Analysis in Heterogeneous Distributed Coputing Systes: A Heuristic Approach P. K. Yadav Central Building Research Institute, Rooree- 247667, Uttarahand (INDIA)
More informationEnergy Proportionality for Disk Storage Using Replication
Energy Proportionality for Disk Storage Using Replication Jinoh Ki and Doron Rote Lawrence Berkeley National Laboratory University of California, Berkeley, CA 94720 {jinohki,d rote}@lbl.gov Abstract Energy
More informationAn Integrated Approach for Monitoring Service Level Parameters of Software-Defined Networking
International Journal of Future Generation Counication and Networking Vol. 8, No. 6 (15), pp. 197-4 http://d.doi.org/1.1457/ijfgcn.15.8.6.19 An Integrated Approach for Monitoring Service Level Paraeters
More informationEfficient Key Management for Secure Group Communications with Bursty Behavior
Efficient Key Manageent for Secure Group Counications with Bursty Behavior Xukai Zou, Byrav Raaurthy Departent of Coputer Science and Engineering University of Nebraska-Lincoln Lincoln, NE68588, USA Eail:
More informationAdaptive Modulation and Coding for Unmanned Aerial Vehicle (UAV) Radio Channel
Recent Advances in Counications Adaptive odulation and Coding for Unanned Aerial Vehicle (UAV) Radio Channel Airhossein Fereidountabar,Gian Carlo Cardarilli, Rocco Fazzolari,Luca Di Nunzio Abstract In
More informationA Soft Real-time Scheduling Server on the Windows NT
A Soft Real-tie Scheduling Server on the Windows NT Chih-han Lin, Hao-hua Chu, Klara Nahrstedt Departent of Coputer Science University of Illinois at Urbana Chapaign clin2, h-chu3, klara@cs.uiuc.edu Abstract
More informationA CHAOS MODEL OF SUBHARMONIC OSCILLATIONS IN CURRENT MODE PWM BOOST CONVERTERS
A CHAOS MODEL OF SUBHARMONIC OSCILLATIONS IN CURRENT MODE PWM BOOST CONVERTERS Isaac Zafrany and Sa BenYaakov Departent of Electrical and Coputer Engineering BenGurion University of the Negev P. O. Box
More informationINTEGRATED ENVIRONMENT FOR STORING AND HANDLING INFORMATION IN TASKS OF INDUCTIVE MODELLING FOR BUSINESS INTELLIGENCE SYSTEMS
Artificial Intelligence Methods and Techniques for Business and Engineering Applications 210 INTEGRATED ENVIRONMENT FOR STORING AND HANDLING INFORMATION IN TASKS OF INDUCTIVE MODELLING FOR BUSINESS INTELLIGENCE
More informationWorkflow Management in Cloud Computing
Workflow Manageent in Cloud Coputing Monika Bharti M.E. student Coputer Science and Engineering Departent Thapar University, Patiala Anju Bala Assistant Professor Coputer Science and Engineering Departent
More informationA Study on the Chain Restaurants Dynamic Negotiation Games of the Optimization of Joint Procurement of Food Materials
International Journal of Coputer Science & Inforation Technology (IJCSIT) Vol 6, No 1, February 2014 A Study on the Chain estaurants Dynaic Negotiation aes of the Optiization of Joint Procureent of Food
More informationPREDICTION OF POSSIBLE CONGESTIONS IN SLA CREATION PROCESS
PREDICTIO OF POSSIBLE COGESTIOS I SLA CREATIO PROCESS Srećko Krile University of Dubrovnik Departent of Electrical Engineering and Coputing Cira Carica 4, 20000 Dubrovnik, Croatia Tel +385 20 445-739,
More informationCalculation Method for evaluating Solar Assisted Heat Pump Systems in SAP 2009. 15 July 2013
Calculation Method for evaluating Solar Assisted Heat Pup Systes in SAP 2009 15 July 2013 Page 1 of 17 1 Introduction This docuent describes how Solar Assisted Heat Pup Systes are recognised in the National
More informationInformation Processing Letters
Inforation Processing Letters 111 2011) 178 183 Contents lists available at ScienceDirect Inforation Processing Letters www.elsevier.co/locate/ipl Offline file assignents for online load balancing Paul
More informationLoad Control for Overloaded MPLS/DiffServ Networks during SLA Negotiation
Int J Counications, Network and Syste Sciences, 29, 5, 422-432 doi:14236/ijcns292547 Published Online August 29 (http://wwwscirporg/journal/ijcns/) Load Control for Overloaded MPLS/DiffServ Networks during
More informationInsurance Spirals and the Lloyd s Market
Insurance Spirals and the Lloyd s Market Andrew Bain University of Glasgow Abstract This paper presents a odel of reinsurance arket spirals, and applies it to the situation that existed in the Lloyd s
More informationREQUIREMENTS FOR A COMPUTER SCIENCE CURRICULUM EMPHASIZING INFORMATION TECHNOLOGY SUBJECT AREA: CURRICULUM ISSUES
REQUIREMENTS FOR A COMPUTER SCIENCE CURRICULUM EMPHASIZING INFORMATION TECHNOLOGY SUBJECT AREA: CURRICULUM ISSUES Charles Reynolds Christopher Fox reynolds @cs.ju.edu fox@cs.ju.edu Departent of Coputer
More informationData Streaming Algorithms for Estimating Entropy of Network Traffic
Data Streaing Algoriths for Estiating Entropy of Network Traffic Ashwin Lall University of Rochester Vyas Sekar Carnegie Mellon University Mitsunori Ogihara University of Rochester Jun (Ji) Xu Georgia
More informationA Fast Algorithm for Online Placement and Reorganization of Replicated Data
A Fast Algorith for Online Placeent and Reorganization of Replicated Data R. J. Honicky Storage Systes Research Center University of California, Santa Cruz Ethan L. Miller Storage Systes Research Center
More informationEndogenous Credit-Card Acceptance in a Model of Precautionary Demand for Money
Endogenous Credit-Card Acceptance in a Model of Precautionary Deand for Money Adrian Masters University of Essex and SUNY Albany Luis Raúl Rodríguez-Reyes University of Essex March 24 Abstract A credit-card
More informationADJUSTING FOR QUALITY CHANGE
ADJUSTING FOR QUALITY CHANGE 7 Introduction 7.1 The easureent of changes in the level of consuer prices is coplicated by the appearance and disappearance of new and old goods and services, as well as changes
More informationApproximately-Perfect Hashing: Improving Network Throughput through Efficient Off-chip Routing Table Lookup
Approxiately-Perfect ing: Iproving Network Throughput through Efficient Off-chip Routing Table Lookup Zhuo Huang, Jih-Kwon Peir, Shigang Chen Departent of Coputer & Inforation Science & Engineering, University
More informationPreference-based Search and Multi-criteria Optimization
Fro: AAAI-02 Proceedings. Copyright 2002, AAAI (www.aaai.org). All rights reserved. Preference-based Search and Multi-criteria Optiization Ulrich Junker ILOG 1681, route des Dolines F-06560 Valbonne ujunker@ilog.fr
More information- 265 - Part C. Property and Casualty Insurance Companies
Part C. Property and Casualty Insurance Copanies This Part discusses proposals to curtail favorable tax rules for property and casualty ("P&C") insurance copanies. The syste of reserves for unpaid losses
More informationPerformance Evaluation of Machine Learning Techniques using Software Cost Drivers
Perforance Evaluation of Machine Learning Techniques using Software Cost Drivers Manas Gaur Departent of Coputer Engineering, Delhi Technological University Delhi, India ABSTRACT There is a treendous rise
More informationSAMPLING METHODS LEARNING OBJECTIVES
6 SAMPLING METHODS 6 Using Statistics 6-6 2 Nonprobability Sapling and Bias 6-6 Stratified Rando Sapling 6-2 6 4 Cluster Sapling 6-4 6 5 Systeatic Sapling 6-9 6 6 Nonresponse 6-2 6 7 Suary and Review of
More informationTHINKSERVER OS AND VIRTUALIZATION OPTIONS
THINKSERVER OS AND VIRTUALIZATION OPTIONS MICROSOFT WINDOWS SERVER 2012: THE NEW ENTERPRISE STANDARD You rely on ThinkServer racks and servers to power your business-critical deployents because you trust
More informationCOMBINING CRASH RECORDER AND PAIRED COMPARISON TECHNIQUE: INJURY RISK FUNCTIONS IN FRONTAL AND REAR IMPACTS WITH SPECIAL REFERENCE TO NECK INJURIES
COMBINING CRASH RECORDER AND AIRED COMARISON TECHNIQUE: INJURY RISK FUNCTIONS IN FRONTAL AND REAR IMACTS WITH SECIAL REFERENCE TO NECK INJURIES Anders Kullgren, Maria Krafft Folksa Research, 66 Stockhol,
More informationEnrolment into Higher Education and Changes in Repayment Obligations of Student Aid Microeconometric Evidence for Germany
Enrolent into Higher Education and Changes in Repayent Obligations of Student Aid Microeconoetric Evidence for Gerany Hans J. Baugartner *) Viktor Steiner **) *) DIW Berlin **) Free University of Berlin,
More informationESTIMATING LIQUIDITY PREMIA IN THE SPANISH GOVERNMENT SECURITIES MARKET
ESTIMATING LIQUIDITY PREMIA IN THE SPANISH GOVERNMENT SECURITIES MARKET Francisco Alonso, Roberto Blanco, Ana del Río and Alicia Sanchis Banco de España Banco de España Servicio de Estudios Docuento de
More informationEquivalent Tapped Delay Line Channel Responses with Reduced Taps
Equivalent Tapped Delay Line Channel Responses with Reduced Taps Shweta Sagari, Wade Trappe, Larry Greenstein {shsagari, trappe, ljg}@winlab.rutgers.edu WINLAB, Rutgers University, North Brunswick, NJ
More informationProducts vs. Advertising: Media Competition and the. Relative Source of Firm Profits
Products vs. Advertising: Media Copetition and the Relative Source of Fir Profits David Godes, Elie Ofek and Miklos Sarvary February 2003 The authors would like to thank Dina Mayzlin, and participants
More informationAutoHelp. An 'Intelligent' Case-Based Help Desk Providing. Web-Based Support for EOSDIS Customers. A Concept and Proof-of-Concept Implementation
//j yd xd/_ ' Year One Report ":,/_i',:?,2... i" _.,.j- _,._".;-/._. ","/ AutoHelp An 'Intelligent' Case-Based Help Desk Providing Web-Based Support for EOSDIS Custoers A Concept and Proof-of-Concept Ipleentation
More informationResearch on Risk Assessment of PFI Projects Based on Grid-fuzzy Borda Number
Researc on Risk Assessent of PFI Projects Based on Grid-fuzzy Borda Nuber LI Hailing 1, SHI Bensan 2 1. Scool of Arcitecture and Civil Engineering, Xiua University, Cina, 610039 2. Scool of Econoics and
More informationLocal Area Network Management
Technology Guidelines for School Coputer-based Technologies Local Area Network Manageent Local Area Network Manageent Introduction This docuent discusses the tasks associated with anageent of Local Area
More informationOn Computing Nearest Neighbors with Applications to Decoding of Binary Linear Codes
On Coputing Nearest Neighbors with Applications to Decoding of Binary Linear Codes Alexander May and Ilya Ozerov Horst Görtz Institute for IT-Security Ruhr-University Bochu, Gerany Faculty of Matheatics
More informationFactored Models for Probabilistic Modal Logic
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008 Factored Models for Probabilistic Modal Logic Afsaneh Shirazi and Eyal Air Coputer Science Departent, University of Illinois
More informationPhysics 211: Lab Oscillations. Simple Harmonic Motion.
Physics 11: Lab Oscillations. Siple Haronic Motion. Reading Assignent: Chapter 15 Introduction: As we learned in class, physical systes will undergo an oscillatory otion, when displaced fro a stable equilibriu.
More informationEvaluating the Effectiveness of Task Overlapping as a Risk Response Strategy in Engineering Projects
Evaluating the Effectiveness of Task Overlapping as a Risk Response Strategy in Engineering Projects Lucas Grèze Robert Pellerin Nathalie Perrier Patrice Leclaire February 2011 CIRRELT-2011-11 Bureaux
More informationUsing Bloom Filters to Refine Web Search Results
Using Bloo Filters to Refine Web Search Results Navendu Jain Departent of Coputer Sciences University of Texas at Austin Austin, TX, 78712 nav@cs.utexas.edu Mike Dahlin Departent of Coputer Sciences University
More informationAn Application Research on the Workflow-based Large-scale Hospital Information System Integration
106 JOURNAL OF COMPUTERS, VOL. 6, NO. 1, JANUARY 2011 An Application Research on the Workflow-based Large-scale Hospital Inforation Syste Integration Yang Guojun School of Coputer, Neijiang Noral University,
More information